Functional inequalities for forward and backward diffusions

Daniel Bartl, Ludovic Tangpi

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


In this article we derive Talagrand’s T2 inequality on the path space w.r.t. the maximum norm for various stochastic processes, including solutions of one-dimensional stochastic differential equations with measurable drifts, backward stochastic differential equations, and the value process of optimal stopping problems. The proofs do not make use of the Girsanov method, but of pathwise arguments. These are used to show that all our processes of interest are Lipschitz transformations of processes which are known to satisfy desired functional inequalities.

Original languageAmerican English
Article number94
Pages (from-to)1-22
Number of pages22
JournalElectronic Journal of Probability
StatePublished - 2020

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


  • Backward stochastic differential equation
  • Concentration of measures
  • Logarithmic-Sobolev inequality
  • Non-smooth coefficients
  • Optimal stopping
  • Quadratic transportation inequality
  • Stochastic differential equation


Dive into the research topics of 'Functional inequalities for forward and backward diffusions'. Together they form a unique fingerprint.

Cite this